Large Scale Legal Text Classification Using Transformer Models

Large multi-label text classification is a challenging Natural Language Processing (NLP) problem that is concerned with text classification for datasets with thousands of labels. We tackle this problem in the legal domain, where datasets, such as JRC-Acquis and EURLEX57K labeled with the EuroVoc voc...

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Veröffentlicht in:	arXiv.org 2020-10
Hauptverfasser:	Shaheen, Zein, Wohlgenannt, Gerhard, Filtz, Erwin
Format:	Artikel
Sprache:	eng
Schlagworte:	Ablation Algorithms Classification Datasets Information systems Iterative methods Natural language processing Taxonomy Transformers
Online-Zugang:	Volltext
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